About Me

I am currently a research fellow at the Harvard Quantum Initiative (HQI), specializing in quantum information theory and machine learning I work closely with experimentalists across a variety of quantum platforms—including neutral atom tweezer arrays, optical lattices, and superconducting qubits—where I have designed experimental protocols that have been successfully implemented for a broad range of quantum information processing tasks.

My interests lie in both near-term and fault-tolerant applications of programmable quantum systems including 1. analog and digital quantum simulation; 2. quantum statistical learning, such as Hamiltonian learning, device benchmarking, and quantum state learning; 3. quantum optimal control for efficient gate design; 4. machine learning for quantum information science, such as automated error correction code design and efficient decoders for quantum error correction codes.

By combining tools from quantum information theory, quantum optimal control, and machine learning, I aim to advance the capabilities of quantum technologies and the understanding of quantum many-body systems.

Research Topics

• Quantum Simulation: Analog and digital simulation of many-body quantum systems using programmable quantum platforms such as neutral atom arrays, optical lattices, and superconducting circuits.
• Quantum Statistical Learning: Scalable methods for Hamiltonian learning, device characterization, randomized benchmarking, and quantum state tomography.
• Quantum Optimal Control: Design and implementation of optimal pulse sequences for high-fidelity gate operations, especially under experimental constraints in neutral atoms, optical lattices, and superconducting platforms.
• Machine Learning for Quantum Information: Development of ML-based tools for efficient learning and control of quantum systems, which includes automated QEC code design and efficient decoding algorithms.
• Efficient Quantum Information Processing with Atom Arrays: Leveraging the flexibility and programmability of Rydberg atom arrays for scalable and expressive quantum computation.
• Randomized Measurement Toolbox: Designing and applying randomized measurement protocols for efficient state and process estimation, error mitigation, and hybrid analog-digital quantum computing.
• Noise-Robust Quantum Protocols: Developing methods that remain accurate and sample-efficient under realistic noise, including error mitigation strategies.
• Foundations and Applications of Quantum Information Theory: Theoretical understanding of quantum entanglement, computational complexity, and information-theoretic limits of near-term quantum devices
• Quantum Machine Learning Theory: Theoretical understanding of quantum advantage in learning tasks, including unconditional quantum advantage rooted in quantum entanglement, nonlocality, and contextuality.

Honors

• Fellow of Harvard Quantum Initiative

• Nominee of UC's President Dissertation Year Fellow by the Physics Department (2021)
• Chair's Challenge Award recipient, UCSD Physics Department. (2018)
• Honor title: ​Weiming scholar, Peking University. (2013-2016)
• Honor title: College Graduate Excellence Award of Beijing City. Ministry of Education. (2016)
• Gold Medal, China Undergraduate Physics Tournament, Peking University Team (2013)

Community Service

I am an active reviewer for: 

• Nature Communications
• npj Quantum Information
• Physical Review X Quantum
• Physical Review Letters
• Physical Review Research
• Quantum
• Machine Learning Science and Technology
• Quantum Science and Technology
• TQC conference
• AQIS conference
• QIP conference

My Career

• Sept. 2022 - Present: Harvard Quantum Initiative & Harvard-MIT Center for Ultracold Atoms (Postdoc Fellow)
• Jun. 2022 - Aug. 2022:  QuEra Computing Inc. (Quantum Algorithm Consultant).
• Jun. 2021 - Jun. 2022: NASA Quantum AI and USRA (Feynman Quantum Academy Intern)
• Mar. 2016 - Mar. 2022: PhD, University of California, San Diego, USA
• Sept. 2016 - Mar. 2018: Salk Institute for Biological Studies (Research assistant)
• Sept. 2012- Jun. 2016: BS, Peking University, China